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NASA NTRS1981

A study of atmospheric diffusion from the LANDSAT imagery

LANDSAT multispectral scanner data of the smoke plumes which originated in eastern Cabo Frio, Brazil and crossed over into the Atlantic Ocean, are analyzed to illustrate how high resolution LANDSAT imagery can aid meteorologists in evaluating specific air pollution events. The eleven LANDSAT images selected are for different months and years. The results show that diffusion is governed primarily by water and air temperature differences. With colder water, low level air is very stable and the vertical diffusion is minimal; but water warmer than the air induces vigorous diffusion. The applicability of three empirical methods for determining the horizontal eddy diffusivity coefficient in the Gaussian plume formula was evaluated with the estimated standard deviation of the crosswind distribution of material in the plume from the LANDSAT imagery. The vertical diffusion coefficient in stable conditions is estimated using Weinstock's formulation. These results form a data base for use in the development and validation of meso scale atmospheric diffusion models.

Dejesusparada, N.↗
NASA NTRS1971

A Method for Monitoring Organic Chlorides, Hydrochloric Acid and Chlorine in Air

While not commonly presented in nonurban atmospheres, organic chlorides, hydrochloric acid and chlorine are significant in industrial air pollution and industrial hygiene. Based on a microcoulometer, a much more sensitive method than has heretofore been available has been developed for monitoring these air impurities. The method has a response time (90%) of about twenty seconds, requires no calibration, is accurate to +/- 2.5%, and specific except for bromide and iodide interferences. The instrument is portable and has been operated unattended for 18 hours without difficulty.

Dennison, J. E.↗
NASA NTRS2020

Application of Low-Cost Fine Particulate Mass Monitors to Convert Satellite Aerosol Optical Depth Measurements to Surface Concentrations in North America and Africa

Low-cost particulate mass sensors provide opportunities to assess air quality at unprecedented spatial and temporal resolutions. Established traditional monitoring networks have limited spatial resolution and are simply absent in many major cities across sub-Saharan Africa (SSA). Satellites provide snapshots of regional air pollution but require ground-truthing. Low-cost monitors can supplement and extend data coverage from these sources worldwide, providing a better overall air quality picture. We investigate the utility of such a multi-source data integration approach using two case studies. First, in Pittsburgh, Pennsylvania, both traditional monitoring and dense low-cost sensor networks are compared with satellite aerosol optical depth (AOD) data from NASA's MODIS system, and a linear conversion factor is developed to convert AOD to surface fine particulate matter mass concentration (as PM2.5). With 10 or more ground monitors in Pittsburgh, there is a 2-fold reduction in surface PM2.5 estimation mean absolute error compared to using only a single ground monitor. Second, we assess the ability of combined regional-scale satellite retrievals and local-scale low-cost sensor measurements to improve surface PM2.5 estimation at several urban sites in SSA. In Rwanda, we find that combining local ground monitoring information with satellite data provides a 40 % improvement in surface PM2.5 estimation accuracy with respect to using low-cost ground monitoring data alone. A linear AOD-to-surface-PM2.5 conversion factor developed in Kigali, Rwanda, did not generalize well to other parts of SSA and varied seasonally for the same location, emphasizing the need for ongoing and localized ground-based monitoring, which can be facilitated by low-cost sensors. Overall, we find that combining ground-based low-cost sensor and satellite data, even without including additional meteorological or land use information, can improve and expand spatiotemporal air quality data coverage, especially in data-sparse regions.

AOD↗
NASA NTRS2026

Timing the Flames: Geostationary Satellite Detection of Diurnally Shifting Stubble Burning in Northwestern India

Post-monsoon open-field stubble burning in northwestern (NW) India—a key agricultural region known as the “breadbasket”—is a longstanding practice used to clear fields. Satellite observations spanning over two decades have revealed significant upward trends in crop production, vegetative greenness, and the frequency of post-harvest fires, with this last contributing to hazardous air quality during the peak burning season (mid-October to mid-November). Since 2022, thermal anomaly data from Aqua-MODIS and SNPP-VIIRS sensors have shown a sharp decline in reported fire events—an observation that contrasts starkly with the concurrent rise in regional aerosol loading detected from space. This apparent discrepancy became particularly pronounced in 2024–2025, prompting a closer examination using high-temporal-resolution imagery from the Advanced Meteorological Imager (AMI) on the geostationary satellite GEO-KOMPSAT-2A. These observations revealed a clear spike in fire-related signals occurring around and after 4:00 p.m. local time, i.e., outside the typical noon to 2:00 p.m. detection window of the MODIS and VIIRS. A fire detection algorithm exploiting the fire-sensitive shortwave-infrared 3.8 μm signal and its contrast to 11.2 μm infrared observations is designed to adopt AMI observations and applied to its multi-year observations (2019–2025). The resulting fire dataset unambiguously shows a gradual shift in stubble burning activity toward the late afternoon hours beginning in 2022 which is underreported by polar-orbiting satellites. The orbital drift of NASA’s MODIS sensor on the Aqua platform allows detection of some of the gradually shifting fires during afternoon hours, but the MODIS still misses a large number of fires occurring around and after 4 p.m. The AMI’s relatively coarse spatial resolution (~4 km), a consequence of its slant viewing geometry over NW India, imposes inherent limitations on quantifying the full extent of fire occurrences. The operational air quality forecasting models currently assimilate satellite fire detections predominantly captured during early afternoon overpasses of the MODIS and VIIRS. The temporal shift in fire activity complicates such forecast, leading to a substantial underestimation of emissions. Intense stubble burning and the resulting air pollution highlight the need for effective crop residue management practices for mitigating the frequency of open biomass burning and thereby reducing episodic degradation of air quality and its associated public health and economic impacts.

post-monsoon stubble burning; northwestern India;↗
NASA NTRS2014

Wildfire Emissions and Their Interaction with Urban and Rural Pollution: Data and Simulations

In recent years NASA has conducted a series of airborne campaigns (e. g. SEAC4RS*, ARCTAS, INTEX-A/B) over North America using an instrumented DC-8 aircraft equipped to measure a very large number of gaseous and aerosol constituents including several unique tracers. In these campaigns wild fires were extensively sampled near source as well as downwind after aging. The data provided detailed information on the composition and chemistry of fire emissions under a variety of atmospheric conditions as well as their interactions with rural and urban air pollution. Major fires studied including the California Rim fire in 2013 (SEAC4RS), the 2008 California wildfires (ARCTAS), and the Alaskan fires downwind over eastern US (INTEX-A). Although some fire plumes contained virtually no O3 enhancement, others showed significant ozone formation. Over Los Angeles, the highest O3 mixing ratios were observed in fire influenced urban air masses. Attempts to simulate these interactions using state of the art models were only minimally successful and indicated several shortcomings in simulating fire emission influences on urban smog formation. A variety of secondary oxidation products (e. g. O3, PAN, HCHO) were substantially underestimated. We will discuss the data collected in fire influenced air masses and their potential air quality implications.

FIre Emissions↗
NASA NTRS2016

Impact of the 2008 Global Recession on Air Quality over the United States: Implications for Surface Ozone Levels from Changes in NOx Emissions

Satellite and ground observations detected large variability in nitrogen oxides (NOx) during the 2008 economic recession, but the impact of the recession on air quality has not been quantified. This study combines observed NOx trends and a regional chemical transport model to quantify the impact of the recession on surface ozone (O3) levels over the continental United States. The impact is quantified by simulating O3 concentrations under two emission scenarios: business-as-usual (BAU) and recession. In the BAU case, the emission projection from the Cross-State Air Pollution Rule is used to estimate the would-be NOx emission level in 2011. In the recession case, the actual NO2 trends observed from Air Quality System ground monitors and the Ozone Monitoring Instrument on the Aura satellite are used to obtain realistic changes in NOx emissions. The model prediction with the recession effect agrees better with ground O3 observations over time and space than the prediction with the BAU emission. The results show that the recession caused a 12ppbv decrease in surface O3 concentration over the eastern United States, a slight increase (0.51ppbv) over the Rocky Mountain region, and mixed changes in the Pacific West. The gain in air quality benefits during the recession, however, could be quickly offset by the much slower emission reduction rate during the post-recession period.

NOx emissions↗
NASA NTRS2004

Comparison of Satellite Observations of Aerosol Optical Depth to Surface Monitor Fine Particle Concentration

Under NASA's Earth Science Applications Program, the Infusing satellite Data into Environmental Applications (IDEA) project examined the relationship between satellite observations and surface monitors of air pollutants to facilitate a more capable and integrated observing network. This report provides a comparison of satellite aerosol optical depth to surface monitor fine particle concentration observations for the month of September 2003 at more than 300 individual locations in the continental US. During September 2003, IDEA provided prototype, near real-time data-fusion products to the Environmental Protection Agency (EPA) directed toward improving the accuracy of EPA s next-day Air Quality Index (AQI) forecasts. Researchers from NASA Langley Research Center and EPA used data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument combined with EPA ground network data to create a NASA-data-enhanced Forecast Tool. Air quality forecasters used this tool to prepare their forecasts of particle pollution, or particulate matter less than 2.5 microns in diameter (PM2.5), for the next-day AQI. The archived data provide a rich resource for further studies and analysis. The IDEA project uses data sets and models developed for tropospheric chemistry research to assist federal, state, and local agencies in making decisions concerning air quality management to protect public health.

Kleb, Mary M.↗
NASA NTRS1999

Investigation of NOx Removal from Small Engine Exhaust

Contribution of emissions from small engines to the air pollution is significant. Due to differences in operating conditions and economics, the pollution control systems designed for automobiles will be neither suitable nor economically feasible for use on small engines. The objective of this project was to find a catalyst for the removal of NOx from the exhaust of small engines which use a rich air to fuel ratio. The desired catalyst should be inexpensive so that the cost of the pollution control unit will be only a small fraction of the total equipment cost. The high cost of noble metals makes them too expensive for use as NOx catalyst for small engines. Catalytic reduction of Nitrogen Oxide (NO) can also be accomplished by base-metal oxide catalysts. The main disadvantage of base-metal catalysts is their deactivation by poisons and high temperatures. Requirements for the length of the life of the small engine exhaust catalysts are much less than those for automobile exhaust catalysts. Since there is no oxygen in the exhaust gases, reduction selectivity is not a problem. Also, the reducing exhaust gases might help prevent the harmful interactions of the catalyst with the support. For these reasons only the supported metal oxide catalysts were investigated in this project.

Akyurtlu, Ates↗
NASA NTRS1999

Investigation of NO(x) Removal from Small Engine Exhaust

Contribution of emissions from small engines to the air pollution is significant. Due to differences in operating conditions and economics, the pollution control systems designed for automobiles will be neither suitable nor economically feasible for use on small engines. The objective of this project was to find a catalyst for the removal of NOx from the exhaust of small engines which use a rich air to fuel ratio. The desired catalyst should be inexpensive so that the cost of the pollution control unit will be only a small fraction of the total equipment cost. The high cost of noble metals makes them too expensive for use as NOx catalyst for small engines. Catalytic reduction of NO can also be accomplished by base-metal oxide catalysts. The main disadvantage of base-metal catalysts is their deactivation by poisons and high temperatures. Requirements for the length of the life of the small engine exhaust catalysts are much less than those for automobile exhaust catalysts. Since there is no oxygen in the exhaust gases, reduction selectivity is not a problem. Also, the reducing exhaust gases might help prevent the harmful interactions of the catalyst with the support. For these reasons only the supported metal oxide catalysts were investigated in this project.

Akyurtlu, Ates↗
NASA NTRS1995

Non-Thermal Removal of Gaseous Pollutants

The removal of fluorine based exhaust gases such as CFC's, PFC's, NF3, and SF6 used for plasma etching of and deposition on semi-conductors is a subject of increasing interest because of safety, air pollution, and global warming issues. Conventional treatment methods for removing exhaust gas pollutants are wet scrubbing, carbon and resin adsorption, catalytic oxidation, and thermal incineration. However, there are drawbacks associated with each of these methods which include difficulties in implementation, problems with the disposal of solid and liquid pollutant waste, large water and fuel consumption, and additional pollutants such as NOx emissions which are generated in thermal incineration processes.

exhaust gases↗
NASA NTRS2021

Polarimetric calibration of the Multi-Angle Imager for Aerosols (MAIA)

NASA’s Multi-Angle Imager for Aerosols (MAIA) mission, under development at the Jet Propulsion Laboratory, is designed to study the adverse health effects of different types of particulate air pollution. Planned for launch in 2023 for a 3-year mission, the MAIA satellite instrument will focus on a selected set of metropolitan target areas, where air quality monitors and health data are available. Aerosol concentration and speciation are inferred from multi-angle measurements of backscattered sunlight in 14 spectral bands from 350-2200 nm, with bands near 442, 645 and 1040 nm measuring the degree (DoLP) and angle of linear polarization (AoLP) in addition to radiance. The pushbroom camera has a ~240-km cross-track field of view with a nadir resolution of ~200 m, and is mounted onto a biaxial gimbal to provide along-track view angles within ±60°, to extend the field of regard to ±48°, and to view the instrument’s onboard calibrator (OBC) and dark target. The OBC consists of a sunlit transmissive diffuser, followed by 12 polarizers at different orientations. MAIA’s polarimetry is implemented using miniature wire grid polarizers on the focal plane array, and dual photoelastic modulators (PEMs) and achromatic quarter-wave plates to rapidly rotate the polarization. The resulting ~26-Hz intensity modulation encodes the linearly polarized and total radiance in each pixel, leaving the DoLP and AoLP insensitive to gain calibration. We report on the polarimetric calibration of the MAIA camera using a vacuum-compatible polarization state generator, consisting of a 1600W Xenon lamp, 12-inch integrating sphere, and rotating high-extinction polarizer. Mueller-matrix-based calibration coefficients for each detector pixel are derived from measurements at multiple polarizer angles, and are used to correct the measurements for instrumental polarization aberrations. Prior to flight, the calibrated MAIA camera is panned across the OBC to characterize its output, using uniform illumination with an irradiance similar to the Sun.

Werne, Thomas↗
NASA NTRS2020

NASA's High-Resolution GEOS Forecasting and Reanalysis Products: Support for TOLNet

Stratospheric intrusions (SIs) the introduction of ozone-rich stratospheric air into the troposphere – have been the interest of decades of research for their link with surface ozone air quality exceedances, especially at the high elevations in the western USA in springtime; however, the impact of SIs in the remaining seasons and over the rest of the USA is less clear. We can expect MERRA-2 to realistically represent both atmospheric dynamics and composition. The operational GEOS weather forecasting system, GEOS-FP, has a similar ozone observing system to MERRA-2, while NASA's new global high-resolution air quality forecast system, GEOS-CF, combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12), simulating a wide range of additional air pollutants and tracers which strengthens this detailed analysis of the intrusions and the sources for the high ozone concentrations. Using a multitude of observational datasets, including lidar, air craft, ozonesondes and air quality monitoring surface sites, in combination with the GEOS forecast and reanalysis products, we aim to provide the public with tools which are available in near-real time to enhance their capability to identify the impact of stratospheric air on surface ozone concentrations separate from anthropogenic sources. In particular, improved understanding of the connections between large-scale climate variability and local-scale dynamically-driven air quality events may support improved seasonal prediction of SI events.

Knowland, K. Emma↗
NASA NTRS2022

WMO Air Quality and Climate Bulletin - No. 2

Ongoing climate change, caused by the accumulation of greenhouse gases in the atmosphere, is happening on a timescale of decades to centuries and is driving environmental changes worldwide. In contrast, the air pollution that occurs near the Earth’s surface happens on a timescale of days to weeks, and across spatial scales that range from local (for example, urban centres) to regional (such as the eastern United States of America, northern India or the Amazon). Despite these wide‑ranging differences, air quality and climate change are strongly interconnected. The WMO Air Quality and Climate Bulletin reports annually on the state of air quality and its connections to climate change, reflecting on the geographical distribution of and changes in the levels of traditional pollutants.

Air quality↗
NASA NTRS2023

Mobile Observations of Ozone and Aerosols in Alabama: Southeastern US Summer Pollution and Coastal Variability

We present a detailed analysis of measurements of ozone (O 3 ) and aerosols collected using multiple platforms and instruments during a 5-day mini-campaign in Alabama, for improving our understanding of the chemistry and air quality in the Southeastern United States. Our study features the first on-road O 3 lidar profiling on highways and the coordinated airborne observations that captured O 3 and aerosol structures associated with synoptic weather conditions, stratospheric intrusions, wildfire smoke transport, and enhancements in urban areas. The Doppler wind lidar data suggest that the vertical structures and variability of O 3 and aerosols at Dauphin Island, a coastal site in the Gulf of Mexico, were related to both the synoptic flow and local-scale land-sea breeze circulation. The onshore gulf breeze, which typically started in the afternoon, helped to quickly dilute air pollutants near the surface, resulting in large gradients toward inland areas. In contrast, gradients were much smaller on days without a gulf breeze. O 3 and humidity were highly anti-correlated in the lower free troposphere, but weakly anti-correlated in the planetary boundary layer (PBL) suggesting more complicated emissions and sink of O 3 in the PBL. Our on-road and airborne measurement strategies to quantify the vertical and horizontal chemical gradients will be useful for future geostationary satellite validation.

Shi Kuang↗
NASA NTRS1996

Second International Airborne Remote Sensing Conference and Exhibition

The conference provided four days of displays and scientific presentations on applications, technology, a science of sub-orbital data gathering and analysis. The twelve displayed aircraft equipped with sophisticated instrumentation represented a wide range of environmental and reconnaissance missions,including marine pollution control, fire detection, Open Skies Treaty verification, thermal mapping, hydrographical measurements, military research, ecological and agricultural observations, geophysical research, atmospheric and meterological observations, and aerial photography. The U.S. Air Force and the On-Site Inspection Agency displayed the new Open Skies Treaty verification Boeing OC 135B that promotes international monitoring of military forces and activities. SRl's Jetstream uses foliage and ground penetrating SAR for forest inventories, toxic waste delineation, and concealed target and buried unexploded ordnance detection. Earth Search Sciences's Gulfstream 1 with prototype miniaturized airborne hyperspectral imaging equipment specializes in accurate mineral differentiation, low-cost hydrocarbon exploration, and nonproliferation applications. John E. Chance and the U.S. Army Corps of Engineers displayed the Bell 2 helicopter with SHOALS that performs hydrographic surveying of navigation projects, coastal environment assessment, and nautical charting surveys. Bechtel Nevada and U.S. DOE displayed both the Beech King AIR B-200 platform equipped to provide first response to nuclear accidents and routine environmental surveillance, and the MBB BO-105 helicopter used in spectral analysis for environmental assessment and military appraisal. NASA Ames Research Center's high-altitude Lockheed ER-2 assists in earth resources monitoring research in atmospheric chemistry, oceanography, and electronic sensors; ozone and greenhouse studies and satellite calibration and data validation. Ames also showcased the Learjet 24 Airborne Observatory that completed missions in Venus cloud cover analysis, Quadantid meteor shower studies, extra-solar far infrared ionic structure lines measurement, Cape Kennedy launch support, and studies in air pollution, The Products and Services Exhibit showcased new sensor and image processing technologies, aircraft data collection services, unmanned vehicle technology, platform equipment, turn-key services, software a workstations, GPS services, publications, and processing and integration systems by 58 exhibitors. The participation of aircraft users and crews provided unique dialogue between those who plan data collection a operate the remote sensing technology, and those who supply the data processing and integration equipment. Research results using hyperspectral imagery, radar and optical sensors, lidar, digital aerial photography, a integrated systems were presented. Major research and development programs and campaigns we reviewed, including CNR's LARA Project and European Space Agency's 1991-1995 Airborne Campaign. The pre-conference short courses addressed airborne video, photogrammetry, hyperspectral data analysis, digital orthophotography, imagery and GIS integration, IFSAR, GPS, and spectrometer calibration.

Source record↗
NASA NTRSDate not supplied

Spaceborne Lidar Retrievals of PM2.5 for Air Quality Studies and Applications

Fine particulate matter (PM2.5) substantially contributes to air pollution and negatively affects human health. While many studies have investigated the use of passive column-integrated aerosol optical depth to infer surface PM2.5, the use of lidar observations for air quality characterization is not nearly as extensive. Lidar measurements are critical, however, due to the vertical aerosol information they provide, including near the surface. In this presentation, we first provide an overview of various lidar-based approaches for estimating PM2.5 concentrations and then discuss how lidar measurements can assist other air quality applications. For example, estimates of PM2.5 have been obtained in a physics-based approach through CALIOP near-surface aerosol extinction retrievals, assumptions on the mass extinction efficiency, and incorporating other parameters (an aerosol hygroscopic growth factor and PM2.5/PM10 ratio). Application of this algorithm over the contiguous United States (CONUS) from 2006 to 2018 yielded larger PM2.5 values over the eastern and western CONUS (~10-15 μg/m³) and lower PM2.5 levels in the central CONUS (~5 μg/m³). These spatial patterns were similar to those from gridded PM2.5 concentrations obtained through in situ measurements at ground stations operated by the US Environmental Protection Agency. In another approach, the Cloud Aerosol Transport System (CATS) lidar was used with the Goddard Earth Observing System (GEOS) model in a 1D ensemble-based variational technique to obtain PM2.5 over the US and Europe, and the spatial patterns of the CATS/GEOS based PM2.5 concentrations generally captured those from surface stations (with corresponding hourly EPA PM2.5 vs CATS PM2.5 statistics of R=0.4 and bias=1.5 μg/m³). In our recent work, as part of the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group, we have applied both the CALIOP and CATS/GEOS based approaches over the highly polluted country of India during the post-monsoon season (September-October 2016). We derived elevated levels of two-month mean PM2.5 (~100 μg/m³) in northern India, especially near New Delhi. These high PM2.5 concentrations in the Indo-Gangetic plain are driven in large part from the seasonal burning of crop residue and meteorological conditions typical at this time of the year, such as low wind speeds and a shallow boundary layer. While the satellite-derived PM2.5 moderately replicates (R = ~0.7-0.9) the spatial variability in the two-month mean of surface in situ PM2.5 from monitoring sites operated by the Central and State Pollution Control Boards, we show results from specific scenes for which there are large deviations between the satellite-derived PM2.5 and in situ measurements. Other current work on this topic focuses on developing PM2.5 estimates using airborne high spectral resolution lidar measurements through machine learning regression algorithms and involves several parameters (e.g., aerosol extinction, color ratio, lidar ratio). Application of this method over major metropolitan areas in the US and Asia have resulted in high correlations (R = 0.93) with surface measurements. This airborne lidar approach can be adapted to spaceborne lidar measurements, and all three of these approaches can be applied to ESA’s EarthCARE Atmospheric Lidar instrument, setting the stage for the future Cloud Aerosol Lidar for Global Scale Observations of the Ocean-Land Atmosphere System (CALIGOLA) mission. Ultimately, beyond estimates of PM2.5, the aerosol vertical distribution from lidars can benefit studies involving passive sensor approaches for PM2.5 proxies (including from geostationary satellites), wildfire smoke plume injection heights, volcanic emissions (e.g., ash height retrievals), and aerosol/air quality model assimilation, evaluation, and forecasts.

Travis D Toth↗
NASA NTRS2019

Connecting Crop Productivity, Residue Fires, and Air Quality over Northern India

Northwestern India is known as the “breadbasket” of the country producing two-thirds of food grains, with wheat and rice as the principal crops grown under the crop rotation system. Agricultural data from India indicates a 25% increase in the post-monsoon rice crop production in Punjab during 2002–2016. NASA’s A-train satellite sensors detect a consistent increase in the vegetation index (net 21%) and post-harvest agricultural fire activity (net ~60%) leading to nearly 43% increase in aerosol loading over the populous Indo-Gangetic Plain in northern India. The ground-level particulate matter (PM2.5) downwind over New Delhi shows a concurrent uptrend of net 60%. The effectiveness of a robust satellite-based relationship between vegetation index—a proxy for crop amounts, and post-harvest fires—a precursor of extreme air pollution events, has been further demonstrated in predicting the seasonal agricultural burning. An efficient crop residue management system is critically needed towards eliminating open field burning to mitigate episodic hazardous air quality over northern India.

Hiren Jethva↗
NASA NTRS2008

Long-term Satellite Observations of Asian Dust Storm: Source, Pathway, and Interannual Variability

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. Outbreaks of Asian dust storms occur often in the arid and semi-arid areas of northwestern China -about 1.6x10(exp 6) square kilometers including the Gobi and Taklimakan deserts- with continuous expanding of spatial coverage. These airborne dust particles, originating in desert areas far from polluted regions, interact with anthropogenic sulfate and soot aerosols emitted from Chinese megacities during their transport over the mainland. Adding the intricate effects of clouds and marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from their sources. Furthermore, these aerosols, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol properties (e.g., optical thickness, single scattering albedo) over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. This new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. Reasonable agreements have been achieved between Deep Blue retrievals of aerosol optical thickness and those directly from AERONET sunphotometers over desert and semi-desert regions. New Deep Blue products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. Long-term satellite measurements (1998 - 2007) from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with the Asian dust storm outbreaks. In addition, monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Hsu, N. Christina↗